CREATE TABLE products( products_id serial, location_id integer, --(not unique) idle_products jsonb --has 1000 elements ('[13,45,8976.....]'::jsonb) ); CREATE EXTENSION btree_gin; CREATE INDEX idx ON products USING GIN(location_id, idle_products);
Take just for example;
products table have millions of rows and 1000 elements in every row in
idle_products column. I am gonna take 25 rows after a query filtering against
SELECT * FROM products WHERE location_id IN (SELECT * FROM unnest(array[1245,456,6342,2,23453]::int)) AND idle_products @> to_jsonb(222) ;
On that query what i want to learn is:
idle_products searched through only this 5 rows by composite gin index and so gain(or does it?) much more performance(because there are only 5×1000 elements in 5 rows in
idle_products column, i mean it will only search through 5 rows using gin composite index) or it is searched through all rows in products table despite filtering against location_id and then reduce(limit) rows into 5 by filtering
location_id column values?
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